Inverse Problems and Data Fusion for crop production applications targeting optimal growth - Fertilization

This work in progress is a contribution to crop growth systems for planning and monitoring of farm activities and practices by farmers. The work outlines the initial findings related to modelling, simulation and visualization techniques for crop growth, specifically targeting the barley crop, such that the crop yield is optimized with respect to several parameters (e.g. high end user value and minimum environmental impact), thus obtaining a sustainable production. The growth process optimization is based on information, including sensor based measurements with sensor quality monitoring, from previous and the present growth season. Initially, references targeting the importance of site specific management for obtaining the objective of yield optimization under the constraint of minimizing the environmental load is pointed to. This is followed by key references on modelling, simulation and visualization of the crop growth process based on information on soil quality, field seeding, spraying/fertilization and environmental information in general. Finally, references to software tools, which could form the basis for an open source platform for a planning and monitoring system for optimal crop growth in multiple application areas are given. The contribution concludes with proposals of research questions to be pursued in the near future.